An attack-resistant hybrid data-privatization method with low information loss


Autoria(s): Singh, Kalpana; Batten, Lynn
Contribuinte(s)

Fernandez-Gago, Carmen

Martinelli, Fabio

Pearson, Siani

Augdo, Issac

Data(s)

01/01/2013

Resumo

We examine a recent proposal for data-privatization by testing it against well-known attacks, we show that all of these attacks successfully retrieve a relatively large (and unacceptable) portion of the original data. We then indicate how the data-privatization method examined can be modified to assist it to withstand these attacks and compare the performance of the two approaches. We also show that the new method has better privacy and lower information loss than the former method.

Identificador

http://hdl.handle.net/10536/DRO/DU:30060714

Idioma(s)

eng

Publicador

Springer

Relação

http://dro.deakin.edu.au/eserv/DU:30060714/evid-trustmanagementvii-2013.pdf

http://dro.deakin.edu.au/eserv/DU:30060714/singh-attackresistant-2013.pdf

http://doi.org/10.1007/978-3-642-38323-6_21

Direitos

2013, Springer

Palavras-Chave #data-privatization #information loss #Chebyshev polynomial #spectral filtering #Bayes-estimated data reconstruction #data mining
Tipo

Book Chapter